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Financial Frauds: Data Mining based Detection – A Comprehensive Survey

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Aastha Bhardwaj, Rajan Gupta

Aastha Bhardwaj and Rajan Gupta. Financial Frauds: Data Mining based Detection – A Comprehensive Survey. International Journal of Computer Applications 156(10):20-28, December 2016. BibTeX

	author = {Aastha Bhardwaj and Rajan Gupta},
	title = {Financial Frauds: Data Mining based Detection – A Comprehensive Survey},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {156},
	number = {10},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {20-28},
	numpages = {9},
	url = {},
	doi = {10.5120/ijca2016912538},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Financial fraud is a global problem and had affected the economy worldwide. Data mining being one of the most effective and powerful tool for detecting financial fraud had been used widely by the business analysts and researchers. This survey paper formalizes different types of financial frauds, summarizes the effective attributes for detecting each type of fraud, and present the latest developments on the use of data mining as a detection tool for financial frauds. The present survey analyses almost all published research work in the field of financial fraud detection for the period of 7 years starting from 2009. Its aim is to help researchers in identifying the suitable variables and data mining techniques by providing the landscape of research platforms for detection of financial fraud.


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Financial fraud, Management fraud, Customer fraud, Task relevant data, Data mining, Credit card fraud, Insurance fraud.